About
Hi, I'm a Fellow at the Gates Foundation working on AI x Health product strategies. My day includes research and development in human-agentic systems, clinical ontology, and AI governance.
I'm based in NYC and received my Bachelor's degree in Computer Science from New York University. I also have a background in software engineering. Feel free to connect with me on LinkedIn.
Dolmabahçe Palace, Istanbul
Experience
AI Fellow @ Gates Foundation
Selected as one of five Gates Fellows (5/4,000+) to pursue research and development of AI platforms for LMICs.
AI Fellow @ Google x Kura Labs
Selected for intensive agentic engineering program focused on building human-agentic enterprise applications.
IAC Fellow @ IAC Corporation
Selected for an immersive program designed to empower the next generation of leaders, creators, innovators, and disruptors.
Mentee @ SEO Career, Protégé
Selected for career accelerator program providing close mentorship connection from leaders at JPMorgan and U.S. Army.
Software Engineering Intern @ Pulp
Developed applications for startup focused on rhetorical analysis, the building block for marketing and AI intelligence.
Software Engineering Intern @ Angi
Developed backend for internal CMS tools for managing landing page content within the home services taxonomy.
Software Engineer @ Flexible AI-Enabled Mechatronic Systems Lab, NYU Tandon School of Engineering
Developed low-latency motion control algorithms and computer vision models for 6-DoF robotic systems.
Research Assistant @ Social Science Division, New York University Abu Dhabi (Prof. Korhan Koçak)
Conducted experiments on long short-term memory (LSTM) neural networks for sociopolitical predictive modeling.
Software Engineering Intern @ People Inc.
Improved user experience for high-traffic brands through contributions to product engineering and machine learning R&D.
Projects
Agentic System with Distributed MCP Servers
Built a multi-agent system for homebuying assistance using LangGraph orchestrator and MCP servers, featuring specialized agents for budgeting, program matching, and neighborhood discovery.
Corpus Pruning for LLM Fine-Tuning Process
Developed pruning algorithms using k-means clustering and embedding-based scoring to reduce corpus size while maintaining semantic integrity, then fine-tuned open-source models for improved efficiency.
Past Events
- January 28-30, 2026: Harvard Medical School Partner Visit at Zitnik Lab
- November 7, 2025: Harvard x MIT Innovation Fund Panel Pitch
- September 13-26, 2025: Google Enterprise Agent Hackathon at Kura Labs
- Summer 2023, 2024: Philanthropy Pitches at IAC Corporation
- Fall 2023: Study Abroad at New York University Abu Dhabi
- February 18-19, 2023: HackNYU Hackathon at NYU Tandon School of Engineering